Field of the Disclosure
The present application relates to image sensors suitable for sensing radiation at visible, ultraviolet (UV), deep UV (DUV), vacuum UV (VUV), extreme UV (EUV), X-ray wavelengths, and for sensing electrons, and to methods for operating such image sensors. The sensors are particularly suitable for use in dark-field inspection systems including those used to inspect photomasks, reticles, and semiconductor wafers.
Related Art
The integrated circuit industry requires inspection tools with increasingly higher sensitivity to detect ever smaller defects and particles whose sizes may be smaller than 20 nm. Those same inspection tools need to be capable of detecting large defects such as scratches and water marks, which may have dimensions ranging from less than 1 μm to multiple mm, and of measuring the wafer surface roughness or haze which may have a peak-to-valley amplitude of a few nm or less than 1 nm.
Small particles, small defects, low contrast defects and low-amplitude roughness scatter light only very weakly. In order to detect small defects or particles on photomasks, reticles, and semiconductor wafers, low-noise sensors are required. Sources of sensor noise include dark current within the sensor, readout noise in the sensor, noise in the electronics that amplifies and digitizes the sensor output signal(s), and noise from external electronics including drivers and controllers that gets coupled into the signal.
Typically inspection systems used in the semiconductor industry are designed to inspect a large area (such as the entire surface of a 300 mm or 450 mm diameter silicon wafer) very quickly, in some cases in one minute or less. Thus the time spent collecting the signal from any one small area of the article being inspected, such as the area corresponding to a single pixel on the sensor, must be very short, in many cases much less than 1 ms.
Increasing the intensity of the light used to illuminate the article being inspected can increase the signal level relative to the noise. However high power densities from the illumination are not only expensive to generate, but they also can degrade the optics of the inspection system and may damage the article being inspected.
An important limitation of prior art CCD sensors and driving circuits can be appreciated by studying FIG. 20. This figure illustrates the timing of the signal readout from a CCD. 1110 represents the output voltage of the sensor as a function of time. 1101 represents the sensor output voltage reset clock voltage as a function of time. The vertical axis represents voltage in arbitrary units and the horizontal axis represents time. The vertical scalings of the output voltage 1110 and the reset clock voltage 1101 are not necessarily equal. The vertical offset in the figure between the output voltage 1110 and the reset clock voltage 1101 is simply for clarity and does not imply that one voltage must be more positive or more negative than the other.
The reset clock 1101 resets the output voltage 1110 so that the signal for the next pixel can be output. When the reset clock 1101 is high (positive) as shown at 1102, the output charge from the prior pixel is discharged so that the output signal settles down to the reset level shown as 1115. Voltage 1110 illustrates several practical issues that can degrade the signal-to-noise ratio and accuracy of the output signal of CCD image sensors, particularly when the sensor is operated at high speed as is required for inspection and metrology applications in semiconductor and related industries. When the reset clock 1101 switches from a low voltage to a high voltage as shown at 1103, some of that voltage swing is coupled to the output signal because the reset transistor is necessarily physically located on the CCD adjacent to the output sensing node. This coupling destabilizes the output signal as shown at 1112. Furthermore when the reset clock goes low as shown at 1104, that high-to-low transition is similarly coupled to the output signal and destabilizes the output signal as shown at 1114. After some time, the output signal settles down and stabilizes at the reset level shown as 1115. When the charge from a pixel is transferred to the output, the voltage decreases from the reference level (because the signal comprises electrons and is, hence, a negative charge) to a level such as 1117. In FIG. 20, level 1117 represents the voltage corresponding to a saturated pixel, i.e. maximum signal, and level 1119 represents the voltage corresponding to a signal level that is significantly less than the maximum. Although not shown, typically there will be some settling time after the transition from the reference level 1115 to the signal level such as 1117 or 1119.
In FIG. 20, the signal in the first pixel is proportional to the difference between voltages 1117 and 1115, and the signal in the second pixel is proportional to the difference between voltages 1115 and 1119. Usually, Correlated Double Sampling (CDS) is used to measure the difference between the reference voltage 1115 and the signal voltage such as 1117 and 1119. Correlated Double Sampling is a well-known technique and is described, for example, by J. R. Janesick, “Scientific Charge-Coupled Devices”, SPIE Press, 2001, pp. 556-561.
As can be appreciated from FIG. 11, when the signal needs to be read out at high speed, such as a speed of about 10 MHz or more, there is only a short time for the output voltage 1110 to settle to the reference voltage 1115 and the signal voltages such as 1117 and 1119. For example at 50 MHz, the total time for one pixel is 20 ns. The reset clock pulses must necessarily be much shorter than this with rise and fall times of, at most, 1-2 ns. Such short pulses with fast rise and fall times necessarily cause significant destabilization of the output signal. Only a few ns are available for the output voltage to settle. In some cases, the signal may not have enough time to fully stabilize, leading to analog image data values (captured charges) having low signal-to-noise ratios due, in part, to this reset clock noise component. In the case of un-patterned (bare) or monitor wafer inspection, read noise from an imaging sensor may be the limiting system noise source. That is, higher resolution sampling (a smaller effective pixel size) by the imaging sensor, can, in some cases, unnecessarily reduce system performance.
Therefore, a need arises for an image sensor capable of detecting low light levels at high speed with high spatial resolution and high signal-to-noise ratio, yet overcoming the above disadvantages.